




"""simple docstring"""




import torch

from diffusers import StableDiffusionPipeline


lowerCAmelCase				:     Dict					=				"""path-to-your-trained-model"""
lowerCAmelCase				:     Any					=				StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")

lowerCAmelCase				:     int					=				"""A photo of sks dog in a bucket"""
lowerCAmelCase				:     Optional[Any]					=				pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save("""dog-bucket.png""")









"""simple docstring"""




def        a__					(							snake_case__ = 10_00							)		->   int:
			lowerCamelCase ,  lowerCamelCase      =   1, 1
			lowerCamelCase      =   2
			while True:
						lowerCamelCase      =   0
						lowerCamelCase      =   fa + fa
						lowerCamelCase ,  lowerCamelCase      =   fa, f
						index += 1
						for _ in str(snake_case__							):
									i += 1
						if i == n:
									break
			return index


if __name__ == "__main__":
					print(solution(int(str(input()).strip())))



